Inductive Loop Detection Systems And Methods

ABSTRACT

Example inductive loop detection systems and methods are described. In one implementation, a method receives image data from a camera of a vehicle and determines a geographic position of the vehicle. Based on the image data and the geographic position of the vehicle, the method determines a location of an inductive loop in a roadway proximate the vehicle. The data associated with the location of the inductive loop is stored in a storage device within the vehicle. For a vehicle, a detectable zone may be determined based on actual or simulated outputs an inductive loop system at various locations relative to the vehicle. While driving, the vehicle is controlled to cause the detectable zone to pass over or stop over a known location of the inductive loop.

TECHNICAL FIELD

The present disclosure relates to vehicular systems and, moreparticularly, to systems and methods that detect the presence of one ormore inductive loops in a roadway.

BACKGROUND

Automobiles and other vehicles provide a significant portion oftransportation for commercial, government, and private entities. Manyvehicle roadways include inductive loop systems that, for example,measure traffic flow and sense vehicle positions on the roadway, such assensing a vehicle waiting to turn in a left turn lane or waiting at anentrance to a bridge or highway entrance ramp. To ensure accuratesensing by the inductive loop system, it is necessary that vehicles arepositioned appropriately when driving over or near the inductive loops.Additionally, to support the functionality of driver assistance systemsand/or autonomous driving systems, it is important to detect theinductive loops so the driver assistance systems and autonomous drivingsystems can properly position the vehicle to be sensed by the inductiveloop systems.

BRIEF DESCRIPTION OF THE DRAWINGS

Non-limiting and non-exhaustive embodiments of the present disclosureare described with reference to the following figures, wherein likereference numerals refer to like parts throughout the various figuresunless otherwise specified.

FIG. 1 is a block diagram illustrating an embodiment of a vehiclecontrol system that includes an automated driving/assistance system.

FIGS. 2A and 2B illustrate example inductive loop systems installed in aroadway.

FIG. 3 is a top view diagram illustrating an embodiment of a vehiclewith multiple cameras.

FIG. 4 is a flow diagram illustrating an embodiment of a method foridentifying and distributing information associated with the location ofinductive loops.

FIG. 5 is a flow diagram illustrating an embodiment of a method foradjusting a vehicle's trajectory to activate an approaching inductiveloop.

FIG. 6 is a flow diagram illustrating an embodiment of a method foridentifying turn lane information and the location of an inductive loopwithin the turn lane.

FIG. 7 is a block diagram illustrating depicting an embodiment of aninductive loop detector.

FIG. 8 is a diagram illustrating the detectability of a vehicle withrespect to location.

FIG. 9 is a process flow diagram of using a location of a detectablezone of a vehicle to activate an inductive loop system.

FIG. 10 is a process flow diagram of a method for controlling trajectoryof a vehicle according to location of a detectable zone and an inductiveloop.

DETAILED DESCRIPTION

In the following description, reference is made to the accompanyingdrawings that form a part thereof, and in which is shown by way ofillustration specific exemplary embodiments in which the disclosure maybe practiced. These embodiments are described in sufficient detail toenable those skilled in the art to practice the concepts disclosedherein, and it is to be understood that modifications to the variousdisclosed embodiments may be made, and other embodiments may beutilized, without departing from the scope of the present disclosure.The following detailed description is, therefore, not to be taken in alimiting sense.

Reference throughout this specification to “one embodiment,” “anembodiment,” “one example,” or “an example” means that a particularfeature, structure, or characteristic described in connection with theembodiment or example is included in at least one embodiment of thepresent disclosure. Thus, appearances of the phrases “in oneembodiment,” “in an embodiment,” “one example,” or “an example” invarious places throughout this specification are not necessarily allreferring to the same embodiment or example. Furthermore, the particularfeatures, structures, databases, or characteristics may be combined inany suitable combinations and/or sub-combinations in one or moreembodiments or examples. In addition, it should be appreciated that thefigures provided herewith are for explanation purposes to personsordinarily skilled in the art and that the drawings are not necessarilydrawn to scale.

Embodiments in accordance with the present disclosure may be embodied asan apparatus, method, or computer program product. Accordingly, thepresent disclosure may take the form of an entirely hardware-comprisedembodiment, an entirely software-comprised embodiment (includingfirmware, resident software, micro-code, etc.), or an embodimentcombining software and hardware aspects that may all generally bereferred to herein as a “circuit,” “module,” or “system.” Furthermore,embodiments of the present disclosure may take the form of a computerprogram product embodied in any tangible medium of expression havingcomputer-usable program code embodied in the medium.

Any combination of one or more computer-usable or computer-readablemedia may be utilized. For example, a computer-readable medium mayinclude one or more of a portable computer diskette, a hard disk, arandom access memory (RAM) device, a read-only memory (ROM) device, anerasable programmable read-only memory (EPROM or Flash memory) device, aportable compact disc read-only memory (CDROM), an optical storagedevice, and a magnetic storage device. Computer program code forcarrying out operations of the present disclosure may be written in anycombination of one or more programming languages. Such code may becompiled from source code to computer-readable assembly language ormachine code suitable for the device or computer on which the code willbe executed.

Embodiments may also be implemented in cloud computing environments. Inthis description and the following claims, “cloud computing” may bedefined as a model for enabling ubiquitous, convenient, on-demandnetwork access to a shared pool of configurable computing resources(e.g., networks, servers, storage, applications, and services) that canbe rapidly provisioned via virtualization and released with minimalmanagement effort or service provider interaction and then scaledaccordingly. A cloud model can be composed of various characteristics(e.g., on-demand self-service, broad network access, resource pooling,rapid elasticity, and measured service), service models (e.g., Softwareas a Service (“SaaS”), Platform as a Service (“PaaS”), andInfrastructure as a Service (“IaaS”)), and deployment models (e.g.,private cloud, community cloud, public cloud, and hybrid cloud).

The flow diagrams and block diagrams in the attached figures illustratethe architecture, functionality, and operation of possibleimplementations of systems, methods, and computer program productsaccording to various embodiments of the present disclosure. In thisregard, each block in the flow diagrams or block diagrams may representa module, segment, or portion of code, which comprises one or moreexecutable instructions for implementing the specified logicalfunction(s). It will also be noted that each block of the block diagramsand/or flow diagrams, and combinations of blocks in the block diagramsand/or flow diagrams, may be implemented by special purposehardware-based systems that perform the specified functions or acts, orcombinations of special purpose hardware and computer instructions.These computer program instructions may also be stored in acomputer-readable medium that can direct a computer or otherprogrammable data processing apparatus to function in a particularmanner, such that the instructions stored in the computer-readablemedium produce an article of manufacture including instruction meanswhich implement the function/act specified in the flow diagram and/orblock diagram block or blocks.

The disclosure relates generally to methods, systems, and apparatusesfor automated or assisted driving and, more particularly, relates toidentification and navigation with respect to inductive loops in aroadway, parking lot or other surface. Inductive loops (also referred toas “induction loops”) are used to detect vehicles passing over orarriving at a particular point on a roadway or other surface. Forexample, inductive loops are used to detect vehicles approaching anintersection, entering a left-turn lane, and entering a freeway entranceramp. Additionally, inductive loops are used to monitor traffic flow andtraffic density by counting the number of vehicles that drive over aninductive loop during a particular time period. This traffic flow andtraffic density information is useful in metering the flow of newtraffic onto a roadway and diverting traffic to different roadways whentraffic density exceeds a particular level.

An inductive loop is an electrically conducting loop installed in thepavement or other driving surface. A data collection system (or otherdevice) transmits energy into the conducting loop. When a vehicle passesover the inductive loop, or stops over the inductive loop, the vehiclecauses a decrease in the inductance, which is sensed by the datacollection system. In some situations, a vehicle must be properlypositioned with respect to the inductive loop to “activate” the loopsuch that the data collection system senses the vehicle. For example, aninductive loop intended to detect vehicles waiting at a traffic signalrequires a vehicle to be positioned at least partially over theinductive loop. If the vehicle is too far away from the inductive loop(e.g., the vehicle has not driven close enough to the traffic signal),the vehicle fails to activate the inductive loop and the existence ofthe waiting vehicle is never detected by the data collection system.Thus, it is important for autonomous and driver-assisted vehicles toknow the location of inductive loops so the vehicle can be navigated toensure activation of the appropriate inductive loops.

The present disclosure describes systems, methods, and devices fordetecting inductive loops in a roadway or other surface. According toone embodiment, a method receives image data from at least one camera ofa vehicle. The method also determines a geographic position of thevehicle. Based on the image data and the geographic position of thevehicle, the method determines a location of an inductive loop in aroadway. The location of the inductive loop is stored in a storagedevice within the vehicle. The location of the inductive loop may alsobe communicated to a central storage system that is accessible bymultiple other vehicles.

FIG. 1 is a block diagram illustrating an embodiment of a vehiclecontrol system 100 may be used to detect inductive loops in a roadway.An automated driving/assistance system 102 may be used to automate orcontrol operation of a vehicle or to provide assistance to a humandriver. For example, the automated driving/assistance system 102 maycontrol one or more of braking, steering, acceleration, lights, alerts,driver notifications, radio, or any other auxiliary systems of thevehicle. In another example, the automated driving/assistance system 102may not be able to provide any control of the driving (e.g., steering,acceleration, or braking), but may provide notifications and alerts toassist a human driver in driving safely. The automateddriving/assistance system 102 may include an inductive loop detector 104that uses a neural network, or other model or algorithm, to determinethat an inductive loop is present in a roadway and may also determinethe location of the inductive loop. In one embodiment, the automateddriving/assistance system 102 may determine a driving maneuver ordriving path to ensure that the vehicle activates the inductive loop asthe vehicle drives over the inductive loop.

The vehicle control system 100 also includes one or more sensorsystems/devices for detecting a presence of nearby objects ordetermining a location of a parent vehicle (e.g., a vehicle thatincludes the vehicle control system 100). For example, the vehiclecontrol system 100 may include radar systems 106, one or more LIDARsystems 108, one or more camera systems 110, a global positioning system(GPS) 112, and/or ultra sound systems 114. The vehicle control system100 may include a data store 116 for storing relevant or useful data fornavigation and safety, such as map data, driving history, or other data.The vehicle control system 100 may also include a transceiver 118 forwireless communication with a mobile or wireless network, othervehicles, infrastructure, or any other communication system. In theembodiment of FIG. 1, transceiver 118 may communicate data to and from acentral storage system 126, such as data associated with inductive loopsand other roadway-related information.

The vehicle control system 100 may include vehicle control actuators 120to control various aspects of the driving of the vehicle such aselectric motors, switches or other actuators, to control braking,acceleration, steering or the like. The vehicle control system 100 mayalso include one or more displays 122, speakers 124, or other devices sothat notifications to a human driver or passenger may be provided. Adisplay 122 may include a heads-up display, dashboard display orindicator, a display screen, or any other visual indicator, which may beseen by a driver or passenger of a vehicle. The speakers 124 may includeone or more speakers of a sound system of a vehicle or may include aspeaker dedicated to driver notification.

It will be appreciated that the embodiment of FIG. 1 is given by way ofexample only. Other embodiments may include fewer or additionalcomponents without departing from the scope of the disclosure.Additionally, illustrated components may be combined or included withinother components without limitation.

In one embodiment, the automated driving/assistance system 102 isconfigured to control driving or navigation of a parent vehicle. Forexample, the automated driving/assistance system 102 may control thevehicle control actuators 120 to drive a path on a road, parking lot,driveway or other location. For example, the automateddriving/assistance system 102 may determine a path based on informationor perception data provided by any of the components 106-118. The sensorsystems/devices 106-110 and 114 may be used to obtain real-time sensordata so that the automated driving/assistance system 102 can assist adriver or drive a vehicle in real-time. The automated driving/assistancesystem 102 may implement an algorithm or use a model, such as a deepneural network, to process the sensor data and identify a presence andlocation of an inductive loop.

FIGS. 2A and 2B illustrate example inductive loop systems installed in aroadway. FIG. 2A illustrates a roadway 200 that includes a lane 202,which is bounded by lane markings 204 and 206. In this example, lanemarking 204 separates traffic in an oncoming lane and lane marking 206identifies the edge of roadway 200. An inductive loop 208 is positionedin the middle of lane 202 such that vehicles driving in lane 202activate inductive loop 208 as they drive over the inductive loop. Adata collection system 210 is coupled to inductive loop 208 and sensesvehicles that drive over inductive loop 208 or stop such that thevehicle is located over at least a portion of inductive loop 208. Insome embodiments, data collection system 210 counts the number ofvehicles that drive over inductive loop 208 during a particular timeperiod. In other embodiments, data collection system 210 senses when avehicle stops over at least a portion of inductive loop 208 and, inresponse, activates a traffic signal, gate, metering light, and thelike.

FIG. 2B illustrates a roadway 220 that includes a lane 222, which isbounded by lane markings 224 and 226. In this example, lane marking 224separates traffic in an oncoming lane and lane marking 226 identifiesthe edge of roadway 220. Two inductive loops 228 and 230 are positionedin the middle of lane 222 such that vehicles driving in lane 222activate inductive loops 228 and 230 as the vehicle drives over theinductive loop. A data collection system 232 is coupled to inductiveloops 228 and 230. Data collection system 232 senses vehicles that driveover inductive loops 228 and 230, or stop such that the vehicle islocated over at least a portion of inductive loop 228 or 230.

Although FIGS. 2A and 2B illustrate particular inductive loop shapes andpositions, other embodiments may include inductive loops having anyshape and positioned in any part of a road surface. For example,inductive loops may have a shape that is round, oval, square,rectangular or a pentagon, hexagon, octagon, and the like. Additionally,the shape of an inductive loop may be irregular. In some embodiments, aninductive loop is positioned in multiple lanes of a roadway. Further,any number of inductive loops may be positioned in close succession. Asshown in FIG. 2B, two inductive loops 228 and 230 are positioned closeto one another. In other embodiments, any number of inductive loops canbe positioned near each other.

FIG. 3 is a top view diagram illustrating an embodiment of a vehicle 300with multiple cameras. In the embodiment of FIG. 3, vehicle 300 has fourcameras 302, 304, 306, and 308. As shown, camera 302 is a forward-facingcamera that captures images of the roadway ahead of vehicle 300. Cameras304 and 306 are side-facing cameras that captures images to the left andright of vehicle 300. For example, camera 304 may capture images of theadjacent lane to the left of vehicle 300 and camera 306 may captureimages of the adjacent lane to the right of vehicle 300. In a particularembodiment, cameras 304 and 306 are mounted in (or near) the side-viewmirrors of vehicle 300. Camera 308 is a rear-facing camera that capturesimages of the roadway behind vehicle 300. Camera 308 may also bereferred to as a backup camera. Cameras 302, 304, 306, and 308 arecoupled to automated driving/assistance system 102, as discussed herein.

Although four cameras 302-308 are shown in FIG. 3, a particular vehiclemay have any number of cameras positioned at any location on thevehicle. Cameras 302-308 are capable of capturing images of a roadway onwhich vehicle 300 is driving. These captured images can be analyzed toidentify inductive loops positioned in the roadway, as discussed herein.

In some embodiments, one or more of cameras 302-308 are continuouslycapturing images of the nearby roadway while vehicle 300 is moving.These captured images are analyzed to identify inductive loops in theroadway and record the geographic location of the inductive loops basedon GPS data. As discussed herein, this recorded information regardingthe inductive loops is communicated to central storage system 126 foruse by other vehicles. In other embodiments, the captured image data andGPS data are communicated to central storage system 126 and a computingsystem (e.g., a server) associated with central storage system 126analyzes the captured images to identify inductive loops in the capturedimage data. Over time, central storage system 126 develops a database ofinductive loop information for roads throughout a region or an entirecountry. This inductive loop information is used by multiple vehicles toidentify approaching inductive loops and locate inductive loops along avehicle's planned route. Thus, multiple vehicles contribute to thedatabase of inductive loop information and receive the benefit ofinductive loop information generated by other vehicles.

FIG. 4 is a flow diagram illustrating an embodiment of a method 400 foridentifying and distributing information associated with the location ofinductive loops. Initially, an inductive loop detector (e.g., inductiveloop detector 104 shown in FIG. 1) receives image data from one or morevehicle cameras at 402. The inductive loop detector also receivesgeographic position information associated with the vehicle at 404. Forexample, the geographic position information provided by GPS 112 may bedetermined and associated with the image data at the time the image datais captured. The inductive loop detector also receives vehicle wheelspeed data at 406. The vehicle wheel speed data may be available fromthe vehicle's CAN (Controller Area Network) bus or directly from a wheelspeed sensor on the vehicle.

The inductive loop detector stores the image data, geographic positioninformation, and wheel speed data at 408. For example, the data andinformation may be stored on a storage device within the vehicle and/orstored on central storage system 126. The inductive loop detector alsodetermines a location of an inductive loop in a roadway based on theimage data and the geographic position information at 410. For example,a camera may capture image data of the roadway and a GPS simultaneouslydetermines a location of the vehicle. In some embodiments, theorientation of the camera is known, such that the area of the roadwaycaptured in the image data is a particular distance and angle from thevehicle. For example, a particular camera may be oriented such that iscaptures an area approximately 5-8 feet behind a vehicle.

Method 400 continues as inductive loop detector communicates thelocation of the inductive loop, image data, geographic positioninformation, and wheel speed data to a central storage system at 412.The location of the inductive loop in the roadway is distributed fromthe central storage system to other vehicles at 414, thereby allowingthe other vehicles to know the location of the inductive loops and drivesuch that the vehicle properly activates the desired inductive loops.

In some embodiments, the described systems and methods also determine acategory associated with a particular roadway, such as a highway, anentrance ramp, a bridge, a left-turn lane, a surface street, and anintersection. This category information is tagged (or otherwiseassociated) with the image data and helps identify a “type” of inductiveloop. For example, an inductive loop in a driving lane of a freeway islikely used to monitor highway traffic flow or traffic density. Aninductive loop on an entrance ramp is likely used to meter traffic(i.e., limit the rate at which vehicles access the entrance ramp). Aninductive loop in a left-turn lane, or near an intersection with atraffic signal, is likely used to notify the traffic signal that avehicle is waiting to turn or continue through an intersection.

In some embodiments, the described systems and methods use deep neuralnetworks that learn to identify inductive loops within image datacaptured by multiple vehicles. For example, deep neural networks may betrained using multiple images (e.g., example inductive loop images)representing different types of inductive loops. As the deep neuralnetworks are trained and gather more data, they become more accurate atidentifying inductive loops within the captured image data. Inparticular implementations, deep neural networks are trained by a humanoperator with knowledge of the image content. The human operator canidentify the location of any inductive loop in each image. The imagedata used during the training contains inductive loops of differentshapes, sizes, orientations, and positions within lanes of a roadway.

After the deep neural networks are trained, they are implemented in aparticular vehicle and/or a separate computing system (e.g., a server)to identify inductive loops in an image. In some embodiments, aninductive loop recognition algorithm first identifies lanes in an imageof a roadway using, for example, lane detection algorithms, digitalmaps, and drive history information. Based on the identified laneinformation, the algorithm defines a region of interest (e.g. the areabetween the lines defining the lane) where inductive loops are likely tobe located. This region of interest is provided to a deep neural networkthat is specifically trained to identify inductive loops. The deepneural network then provides an indication of whether an inductive loopis located within the region of interest. If an inductive loop isdetected, the deep neural network provides position information (i.e.,the specific location of the inductive loop within the region ofinterest).

Many of the example implementations discussed herein use images capturedby one or more vehicle cameras to detect inductive loops in a roadway.In alternate embodiments, other vehicle sensors can be used to detectinductive loops, such as Radar, LIDAR (Light Detection and Ranging),Ultrasound, and the like. In some embodiments, one or more vehiclesensors and/or vehicle camera may be used in combination to detectinductive loops. For example, a vehicle camera can be used incombination with a vehicle's LIDAR system to improve the accuracy ofdetecting inductive loops in a roadway and determining the specificlocation of the inductive loops in the roadway.

FIG. 5 is a flow diagram illustrating an embodiment of a method 500 foradjusting a vehicle's trajectory to activate an approaching inductiveloop. Initially, a vehicle receives information identifying inductiveloops in the proximity of the vehicle and along the vehicle's plannedroute at 502. In some embodiments, the vehicle receives the inductiveloop information, which includes the geographic location of theinductive loop, from central storage system 126. An automateddriving/assistance system in the vehicle determines one or moreinductive loops being approached by the vehicle at 504. For example,based on the vehicle's current location and trajectory (or plannedroute), the automated driving/assistance system can identify upcominginductive loops of interest to the vehicle based on its planned route.

The automated driving/assistance system determines whether the vehicle'scurrent trajectory will activate an approaching inductive loop at 506.If the vehicle will activate the inductive loop at 508, the methodreturns to 504, where the automated driving/assistance system continuesto identify approaching inductive loops. If the vehicle will notactivate the inductive loop at 508, the automated driving/assistancesystem adjusts the vehicle's trajectory to enable activation of theapproaching inductive loop at 510. For example, if the vehicle isapproaching a traffic signal, the method 500 ensures that the vehicleproperly activates an inductive loop responsible for sensing the vehicleand changing the traffic signal to allow the vehicle to proceed throughan intersection.

FIG. 6 is a flow diagram illustrating an embodiment of a method 600 foridentifying turn lane information and the location of an inductive loopwithin the turn lane. Initially, an inductive loop detector receivesimage data from one or more vehicle cameras at 602. The inductive loopdetector also receives geographic position information associated withthe vehicle at 604. Additionally, the inductive loop detector receivesvehicle wheel speed data at 606. The image data, geographic positioninformation, and wheel speed data is stored by the inductive loopdetector at 608.

Method 600 continues as the inductive loop detector identifies anapproaching left-turn lane in a roadway at 610. Although the example ofFIG. 6 discusses a left-turn lane, similar methods may be used withrespect to right-turn lanes, metering lanes, bridge access lanes,traffic signals at intersections, and the like. Regarding the identifiedleft-turn lane, the inductive loop detector determines a location of aninductive loop in the left-turn lane based on the image data at 612.Further, the inductive loop detector determines a length of theleft-turn lane based on the wheel speed data at 614.

Although not shown in FIG. 6, the inductive loop detector maycommunicate the location of the inductive loop, length of the left-turnlane, and other data to a central storage system. The location of theinductive loop and the length of the left-turn lane is then distributedfrom the central storage system to other vehicles, thereby allowing theother vehicles to know the location of the inductive loops and the sizeof the left-turn lane such that the vehicle properly activates thedesired inductive loops.

FIG. 7 is a block diagram illustrating depicting an embodiment ofinductive loop detector 104. As shown in FIG. 7, inductive loop detector104 includes a communication manager 702, a processor 704, and a memory706. Communication manager 702 allows inductive loop detector 104 tocommunicate with other systems, such as automated driving/assistancesystem 102. Processor 704 executes various instructions to implement thefunctionality provided by inductive loop detector 104. Memory 706 storesthese instructions as well as other data used by processor 704 and othermodules contained in inductive loop detector 104.

Additionally, inductive loop detector 104 includes an image analysismodule 708 that identifies inductive loops, lane boundaries, and otherinformation from images captured by one or more cameras attached to thevehicle. A geographic position module 710 determines a geographiclocation of a vehicle when an image is captured by a camera, andassociates the geographic location with the captured image. A wheelspeed analysis module 712 identifies a vehicle's wheel speed and, basedon the wheel speed and the image data, determines a size of a turn laneor other portion of a roadway. A driving maneuver manager 714 determineswhat, if any, changes to the trajectory of a vehicle are necessary toensure that the vehicle activates one or more inductive loops.

Referring to FIG. 8, an inductive loop system detects changes in theinductance of the inductive loop due to presence of conductive orferromagnetic materials in electromagnetic fields created by theinductive loop. This interaction may be due to eddy currents inconductive materials or a change in the permeability around theinductive coil by ferromagnetic materials. Accordingly, for a givenvehicle 800, the detectability of the vehicle by the inductive loop 802varies at various locations under and around the vehicle. This is due tothe variation in the composition of the vehicle. For example, the shadedregions simulate the detectability at various locations relative to thevehicle with the darker shading indicating higher detectability. Thedetectability may be stronger under the engine block and transmissiondue to the large amount of metals whereas other locations are not asdetectable. Accordingly, a zone 804 for a particular vehicle 800indicates where the vehicle is most detectable.

FIG. 9 illustrates a method 900 for determining a detectable zone 804for a particular model or class of vehicle (e.g., sedan, minivan, lighttruck, etc.). As used herein detectable zone 804 does not imply thatother zones of the vehicle 800 are not detectable. Instead, thedetectable zone 804 is an area of higher detectability relative to areasof the vehicle 800 that are not included in the detectable zone 804. Thedetectable zone 804 may be a single position or range of positions, e.g.a square, circle, or other type of shape.

The method 900 may include measuring 902 or calculating inductancechanges over the vehicle underside. This may include parking the vehicle300 at various locations with respect to an inductive loop 802 andmeasuring an output of the inductive loop 802 at each location. Thiswill then result in a two-dimensional map of inductive loop output, suchas that shown in FIG. 8. Alternatively, step 902 may be performed bymodeling. For example, a response of model of an inductive loop in thepresence of a model of the vehicle may be determined usingelectromagnetic modeling techniques, such as finite difference timedomain (FDTD) modeling or other type of modeling technique. In thisapproach, the electromagnetic properties of the components of thevehicle may be defined for the model thereby enabling modeling of thevehicle response with sufficient precision. The simulated response ofthe inductive loop to excitation in the presence of the vehicle modelmay be calculated for various positions of the model of the inductiveloop, thereby obtaining a map of the inductive loop response similar tothat shown in FIG. 8.

The method 900 may further include determining 904 a location andpossibly extent of the detectable zone. For example, the locations atwhich the output in the map is above a threshold may be determined. Aregion that includes these locations may be identified as the detectablezone. Alternatively, an average of these locations may be calculated asa point that is used as the location of the detectable zone.Alternatively, a “center of mass” of the map where the “mass” isrepresented by the output at a given location. For example, the locationof the detectable zone is determined by a weighted average location, theweights applied to each location being the output at that location or afunction of the output at that location.

This detectable zone, either a point or vertices defining a region, maythen be related 906 to a location of the vehicle. For example, a GPSreceiver of the vehicle may be located at a particular location withinthe vehicle. Accordingly, the detectable zone may be defined as anoffset from that location. In other instances, the location of thevehicle may be defined by sensors, e.g. LIDAR (light distancing andranging), RADAR (radio distancing and ranging), or other sensor.Accordingly, the location of the detectable zone may be related to acoordinate system of one or more of these sensors, or a universalcoordinate system to which outputs of these sensors are translated.

The relative position of the detectable zone may then be uploaded 908 toa vehicle controller of one or more actual vehicles corresponding to themodel or class of vehicle that is the subject of the method 900. Forexample, the detectable zone may be stored in a non-transitory memorydevice accessible by the controller during manufacture or transmittedthrough a wireless or wired connection to the vehicle at a time aftermanufacture and/or sale of the vehicle to a consumer.

Referring to FIG. 10, the illustrated method 1000 may be executed by avehicle controller. The method 1000 is particularly useful for anautonomous vehicle. However, it may also be used in a semi-autonomousvehicle, such as in a vehicle providing various driver assist functions,such as an autonomous operation mode that may be activated anddeactivated by the driver.

The method 1000 may include determining 1002 a geographic trajectory ofthe vehicle. This may include determining a street to traverse, turns tomake, and other large scale attributes of a path between the vehicle'scurrent location and a desired destination or waypoint on a path to adestination. Accordingly step 1002 may include executing any navigationalgorithm known in the art, such as using a GPS (global positioningsystem) receiver and routing data.

The method 1000 may further include detecting 1004 lane boundaries of aroad along which the vehicle is traveling and maintaining 1006 thevehicle within a pair of lane boundaries. This may include any techniqueknown in the art of autonomous and semi-autonomous vehicles. Which laneof a plurality of available lanes may be selected based on navigationaldata and adjustments to maintain the vehicle within that lane may beperformed using camera, LIDAR, RADAR, or other data to determine thelocation of the lane with greater precision than the navigational data.

The method 1008 may further include evaluating 1008 whether an inductiveloop lies in the lane along which the vehicle is traveling, e.g. withinX feet ahead of the vehicle along its current trajectory, where X is avalue such as 100 meters or some other value, such as a value thatincreases with the speed of the vehicle. The location of the inductiveloop may be determined and provided to the vehicle according to themethod described above.

If an inductive loop is determined 1008 to be in the lane, the method1000 may include adjusting 1010 the vehicle's trajectory within the lanesuch that the detectable zone passes over the inductive loop. Where thevehicle comes to a stop at an intersection, step 1010 may includecausing the vehicle to come to a stop having the detectable zone overthe inductive loop. For example, where the vehicle location is known,the location of the inductive loop is known, and the relative locationof the detectable zone is known, the vehicle's trajectory may beadjusted such that the vehicle location will be positioned relative tothe inductive loop having the detectable zone over the inductive loop orwithin some threshold distance of the inductive loop.

Although the present disclosure is described in terms of certainpreferred embodiments, other embodiments will be apparent to those ofordinary skill in the art, given the benefit of this disclosure,including embodiments that do not provide all of the benefits andfeatures set forth herein, which are also within the scope of thisdisclosure. It is to be understood that other embodiments may beutilized, without departing from the scope of the present disclosure.

1. A method comprising: receiving, by a driving assistance system in avehicle, information identifying a plurality of inductive loops in theproximity of the vehicle; determining a first inductive loop beingapproached by the vehicle; determining whether a current trajectory ofthe vehicle will activate the first inductive loop; and responsive todetermining that the current trajectory of the vehicle will not activatethe first inductive loop, adjusting the vehicle's trajectory to enableactivation of the first inductive loop.
 2. The method of claim 1,further comprising receiving information identifying inductive loopsalong a planned route of the vehicle.
 3. The method of claim 1, furthercomprising stopping the vehicle at a location that activates the firstinductive loop.
 4. The method of claim 1, wherein the informationidentifying the plurality of inductive loops in the proximity of thevehicle includes a location of the inductive loop within a lane of theroadway.
 5. The method of claim 1, wherein the information identifyingthe plurality of inductive loops in the proximity of the vehicleincludes a location of the inductive loop within a turn lane of theroadway.
 6. The method of claim 1, further comprising: detecting, by thedriving assistance system, lane boundaries of a lane in which thevehicle is traveling; and adjusting, by the driving assistance system,the vehicle's trajectory to both remain within the lane boundaries andto pass over the first inductive loop.
 7. The method of claim 1, furthercomprising: storing, by the driving assistance system, a relativelocation of a detectable zone of the vehicle; wherein adjusting thevehicle's trajectory to enable activation of the first inductive loopcomprises adjusting the vehicle's trajectory such that the detectablezone of the vehicle passes over the first inductive loop.
 8. The methodof claim 7, further comprising: detecting, by the driving assistancesystem, lane boundaries of a lane in which the vehicle is traveling; andadjusting, by the driving assistance system, the vehicle's trajectory toboth remain within the lane boundaries and to cause the detectable zoneto pass over the first inductive loop.
 9. The method of claim 7, furthercomprising causing the vehicle to come to a stop at an intersectionhaving the detectable zone positioned over the first inductive loop. 10.The method of claim 7, further comprising determining the detectablezone by: measuring an output of an inductive coil detection system atvarious relative positions to a test vehicle; determining one or morerelative positions for which the output of the inductive coil detectionsystem meets a threshold condition; and storing a region including theone or more relative positions as the detectable zone.
 11. The method ofclaim 7, further comprising determining the detectable zone by:calculating a simulated output of an inductive coil detection system atvarious relative positions to a model of a test vehicle modelingelectromagnetic properties approximating the vehicle; determining one ormore relative positions for which the simulated output of the inductivecoil detection system meets a threshold condition; storing a regionincluding the one or more relative positions as the detectable zone. 12.A system comprising: a vehicle; and a controller mounted within thevehicle and including one or more processing devices programmed to:receive information identifying a plurality of inductive loops in theproximity of the vehicle; and if a vehicle trajectory is found to passalong an inductive loop of the plurality of inductive loops, adjust thevehicle's trajectory to enable activation of the inductive loop.
 13. Thesystem of claim 12, wherein the one or more processing devices arefurther programmed to: transmit a planned route of the vehicle to aserver system; and receive the information identifying inductive loopsalong the planned route of the vehicle.
 14. The system of claim 12,wherein the one or more processing devices are further programmed tostop the vehicle at a location effective to activate the inductive loop.15. The system of claim 12, wherein the information identifying theplurality of inductive loops in the proximity of the vehicle includes alocation of the inductive loop within a lane of the roadway.
 16. Thesystem of claim 12, wherein the information identifying the plurality ofinductive loops in the proximity of the vehicle includes a location ofthe inductive loop within a turn lane of the roadway.
 17. The system ofclaim 12, further comprising one or more sensors coupled to thecontroller; wherein the one or more processing devices are furtherprogrammed to: detect lane boundaries of a lane in which the vehicle istraveling in outputs of the one or more sensors; and adjust thevehicle's trajectory to both remain within the lane boundaries and topass over the first inductive loop.
 18. The system of claim 12, whereinthe one or more processing devices are further programmed to: store arelative location of a detectable zone of the vehicle; adjust thevehicle's trajectory to enable activation of the inductive loop byadjusting the vehicle's trajectory such that the detectable zone of thevehicle passes over the inductive loop.
 19. The system of claim 18,wherein the one or more processing devices are further programmed to:detect lane boundaries of a lane in which the vehicle is traveling; andadjust the vehicle's trajectory to both remain within the laneboundaries and to cause the detectable zone to pass over the inductiveloop.
 20. The system of claim 18, wherein the one or more processingdevices are further programmed to: cause the vehicle to come to a stopat an intersection having the detectable zone positioned over the firstinductive loop.